- New financial and robo-advisor modules track 13,000 stocks in real time
- Financial reports, earnings data and AI insights now free via Qwen’s deep-dive research service
Alibaba’s AI assistant Qwen upgraded its in-depth research capabilities on April 7, adding financial analysis modules and connecting to 13,000 stocks’ real-time data and roughly one million corporate financial reports.
Unlike peers, which are moving toward paid models due to high computing costs, Qwen is offering the new capabilities free to all users, aiming to narrow the information gap between ordinary investors and professional analysts.
Traditionally, analyzing a company’s earnings required expensive terminals or often scattered, outdated reports—barriers Qwen hopes to remove.
Through a partnership with stock trading platform Tonghuashun, Qwen now integrates what it calls minute-level market data for over 13,000 securities, along with a million reports and filings—roughly equivalent to two decades of work for a single analyst, the company said.
“Usage is heavily PC-based, double that of mobile, showing users treat it as a serious research tool,” a product manager for Qwen’s in-depth research said, speaking on condition of anonymity. “Capital markets have long favored professionals; We hope AI will break down these barriers, rather than create new ones.”
Powered by its Agentic architecture, Qwen autonomously plans and executes analyses. When users request a report, the system parses intent, calls relevant market and financial data, and synthesizes conclusions. Before finalizing, it displays the analytical framework, reducing the “black box” effect often associated with AI usage.
Reports generated through Qwen now offer real-time updates, traceable sources, and detailed financial breakdowns, from valuation changes to cost structures, making sophisticated market research accessible to any investor.
The Yangtzeer reported that Qwen has embedded its AI tasking capabilities across a range of business applications from ride-hailing and booking to enterprise collaboration, in a bid to accelerate adoption of high-level AI assistants.
